The Impact of China’s Lockdown Policy on the Incidence of COVID-19: An Interrupted Time Series Analysis
Author(s) -
Mooketsi Molefi,
John Thato Tlhakanelo,
Thabo Phologolo,
Shimeles Genna Hamda,
Tiny Masupe,
Billy Tsima,
Vincent Setlhare,
Yohana Mashalla,
Douglas J. Wiebe
Publication year - 2021
Publication title -
biomed research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 126
eISSN - 2314-6141
pISSN - 2314-6133
DOI - 10.1155/2021/9498029
Subject(s) - interrupted time series , covid-19 , interrupted time series analysis , incidence (geometry) , confidence interval , counterfactual thinking , china , demography , medicine , statistics , time series , pandemic , mathematics , geography , outbreak , psychological intervention , psychology , virology , disease , infectious disease (medical specialty) , social psychology , geometry , archaeology , psychiatry , sociology
Background Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID-19). In the earlier phases of the emergence of COVID-19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2020. A strategy whose effectiveness in curtailing COVID-19 was yet to be determined. We, therefore, sought to study the impact of the lockdown in reducing the incidence of COVID-19.Methods Daily cases of COVID-19 that occurred in China which were registered between January 12th and March 30th, 2020, were extracted from the Johns Hopkins CSSE team COVID-19 ArcGIS® dashboards. Daily cases reported were used as data points in the series. Two interrupted series models were run: one with an interruption point of 23 January 2020 (model 1) and the other with a 14-day deferred interruption point of 6th February (model 2). For both models, the magnitude of change (before and after) and linear trend analyses were measured, and β -coefficients reported with 95% confidence interval (CI) for the precision.Results Seventy-eight data points were used in the analysis. There was an 11% versus a 163% increase in daily cases in models 1 and 2, respectively, in the preintervention periods ( p ≤ 0.001). Comparing the period immediately following the intervention points to the counterfactual, there was a daily increase of 2,746% ( p < 0.001) versus a decline of 207% ( p = 0.802) in model 2. However, in both scenarios, there was a statistically significant drop in the daily cases predicted for this data and beyond when comparing the preintervention periods and postintervention periods ( p < 0.001).Conclusion There was a significant decrease the COVID-19 daily cases reported in China following the institution of a lockdown, and therefore, lockdown may be used to curtail the burden of COVID-19.
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